Search results for "Artificial Intelligence"
showing 10 items of 6122 documents
Dynamic image denoising for voxel-wise quantification with Statistical Parametric Mapping in molecular neuroimaging.
2018
Purpose PET and SPECT voxel kinetics are highly noised. To our knowledge, no study has determined the effect of denoising on the ability to detect differences in binding at the voxel level using Statistical Parametric Mapping (SPM). Methods In the present study, groups of subject-images with a 10%- and 20%- difference in binding of [123I]iomazenil (IMZ) were simulated. They were denoised with Factor Analysis (FA). Parametric images of binding potential (BPND) were produced with the simplified reference tissue model (SRTM) and the Logan non-invasive graphical analysis (LNIGA) and analyzed using SPM to detect group differences. FA was also applied to [123I]IMZ and [11C]flumazenil (FMZ) clinic…
Realignment of myocardial first-pass MR perfusion images using an automatic detection of the heart-lung interface
2004
International audience; Abstract: Magnetic resonance first-pass imaging of a bolus of contrast agent is well adapted to distinguish normal and hypoperfused areas of the myocardium. In most cases, the signal intensity-time curves in user defined regions of interest (ROI) are studied. As image acquisition is ECG-gated, the images are acquired at the same moment in the cardiac cycle, and the basic shape of the heart is similar from one view to the next. However, superficial respiratory motion can displace the heart in the short-axis plane. The aim of this study is to correct for the respiratory motion of the heart by performing an automatic realignment of the myocardial ROI based on a method t…
An algorithm for oncologic scalp reconstruction.
2010
Background: Modern reconstructive surgery allows for radical resection and reconstruction of any scalp tumor. However, a significant number of patients are still not treated optimally because of incomplete reconstructive guidelines. Methods: The treatment of scalp tumors was documented in 60 patients over a 10-year period. Data regarding tumor type, size, and localization; reconstructive procedure; oncologic, functional, and aesthetic outcome; and complications were collected and analyzed retrospectively. These data were correlated to recurrence and survival rates. The findings extracted from the data were amalgamated to produce the proposed reconstructive algorithm. Results: Five reconstru…
Size invariance in visual number discrimination
1991
This study deals with the observer's ability to discriminate the numerosity of two random dot-patterns irrespective of their relative size. One of these two patterns was a reference one that was always composed of 32 dots randomly distributed within a K x K invisible square window (K = 1.92 degrees). The second one was the test pattern with one of the five magnifications (K = 0.64 degrees, 1.28 degrees, 1.92 degrees, 2.56 degrees, 3.20 degrees) and the relative number of dots varied on 11 levels (N = -15, -12, -9, -6, -3, 0, 3, 6, 9, 12, or 15 dots). The observer's task was to indicate which of the two patterns contained more dots. The results show that the stimulus size, as an irrelevant s…
Validation of ThermoHuman automatic thermographic software for assessing foot temperature before and after running
2020
The aim of the study was to evaluate an automatic thermographic software package (ThermoHuman®) for assessing skin temperature on the soles of the feet before and after running and to compare it with two manual definitions of the regions of interest (ROIs). 120 thermal images of the soles of the feet of 30 participants, at two measurement points (before and after running 30 min) and on two measurement days were analyzed. Three different models of thermographic image analyses were used to obtain the mean temperature of 9 ROIs: A) ThermoHuman (automatic definition of ROIs using ThermoHuman® software), B) Manual (manual delimitation of ROIs by proportion criteria), and C) Manual-TH (manual del…
A deep learning framework for automatic diagnosis of unipolar depression.
2019
Abstract Background and purpose In recent years, the development of machine learning (ML) frameworks for automatic diagnosis of unipolar depression has escalated to a next level of deep learning frameworks. However, this idea needs further validation. Therefore, this paper has proposed an electroencephalographic (EEG)-based deep learning framework that automatically discriminated depressed and healthy controls and provided the diagnosis. Basic procedures In this paper, two different deep learning architectures were proposed that utilized one dimensional convolutional neural network (1DCNN) and 1DCNN with long short-term memory (LSTM) architecture. The proposed deep learning architectures au…
Modeling of Human Posturokinetic Movements by a Linear Feedback System: Relations among Feedback Coefficients
2002
This study describes a method of modeling human trunk and whole body backward bending and suggests a possible neural control strategy. The hypothesis was that the control system can be modeled as a linear feedback system, in which the torque acting at a given joint is a function of the state variables (angular positions and angular velocities). The linear system enabled representation of the feedback system by a gain matrix. The matrix was computed from the kinematics recorded by a movement analysis system and from the joint torques calculated by inverse dynamics. To validate the control model, a comparison was made between the angular kinematics yielded by the model and the experimental d…
A semi-automatic approach for epicardial adipose tissue segmentation and quantification on cardiac CT scans
2019
Abstract Many studies have shown that epicardial fat is associated with a higher risk of heart diseases. Accurate epicardial adipose tissue quantification is still an open research issue. Considering that manual approaches are generally user-dependent and time-consuming, computer-assisted tools can considerably improve the result repeatability as well as reduce the time required for performing an accurate segmentation. Unfortunately, fully automatic strategies might not always identify the Region of Interest (ROI) correctly. Moreover, they could require user interaction for handling unexpected events. This paper proposes a semi-automatic method for Epicardial Fat Volume (EFV) segmentation a…
The influence of scene and object orientation on the scene consistency effect
2019
Abstract Contextual regularities help us make sense of our visual environment. In scenes, semantically consistent objects are typically better recognized than inconsistent ones (e.g., a toaster vs. printer in a kitchen). What is the role of object and scene orientation in this so-called scene consistency effect? We presented consistent and inconsistent objects either upright (Experiment 1) or inverted (rotated 180°; Experiment 2) on upright, inverted, and scrambled background scenes. In Experiment 1, on upright scenes, consistent objects were recognized with higher accuracy than inconsistent ones, and we observed N300/N400 event-related potentials (ERPs) reflecting object-scene semantic pro…
Measuring and modeling real-time responses to music: the dynamics of tonality induction.
2003
We examined a variety of real-time responses evoked by a single piece of music, the organ Duetto BWV 805 by J S Bach. The primary data came from a concurrent probe-tone method in which the probe-tone is sounded continuously with the music. Listeners judged how well the probe tone fit with the music at each point in time. The process was repeated for all probe tones of the chromatic scale. A self-organizing map (SOM) [Kohonen 1997 Self-organizing Maps (Berlin: Springer)] was used to represent the developing and changing sense of key reflected in these judgments. The SOM was trained on the probe-tone profiles for 24 major and minor keys (Krumhansl and Kessler 1982 Psychological Review89 334–…